Simulation Alternatives for Modeling Networked Cyber-Physical Systems

Several embedded system applications are used to control physical processes. Sensing, computation and actuation are combined thus involving a set of highly heterogeneous components, i.e., digital and analog hardware, software, energy sources, and external environment. Moreover, the growing use of networks contributes to introduce a further level of heterogeneity. All these aspects should be taken into account in the design process to find highly optimized solutions, therefore a Cyber-Physical System approach is needed. In particular, simulation is a key technique in the different design stages. However, the heterogeneity of components, together with the presence of the network, forces to adopt complex and slow co-simulation techniques to carry on the simulation of the entire system. This work aims at proposing SystemC as unified framework to model and simulate Networked Cyber-Physical Systems. Concerning the modeling of continuous-time components and a specific class of discrete-time components, the different Models of Computation provided by the Analog/Mixed-Signal (AMS) extension of SystemC are used. Regarding the network, SystemC and the SystemC Network Simulation Library are used to model communications at different abstraction levels. The accuracy and speed of different simulation alternatives are compared by the application to a networked control system.

[1]  Herman Bruyninckx,et al.  Realtime Hybrid Task-Based Control for Robots and Machine Tools , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[2]  Vittorio Zaccaria,et al.  Multicube Explorer: An Open Source Framework for Design Space Exploration of Chip Multi-Processors , 2010, ARCS Workshops.

[3]  Riccardo Muradore,et al.  A SystemC/Matlab co-simulation tool for networked control systems , 2012, Simul. Model. Pract. Theory.

[4]  Franco Fummi,et al.  System/network design-space exploration based on TLM for networked embedded systems , 2010, TECS.

[5]  D.Y. Montuno,et al.  A comparison of active queue management algorithms using the OPNET Modeler , 2002, IEEE Communications Magazine.

[6]  Mo-Yuen Chow,et al.  Networked Control System: Overview and Research Trends , 2010, IEEE Transactions on Industrial Electronics.

[7]  Riccardo Muradore,et al.  A SystemC/Matlab co-simulation tool for networked control systems , 2012 .

[8]  João Pedro Hespanha,et al.  Modeling Communication Networks With Hybrid Systems , 2007, IEEE/ACM Transactions on Networking.

[9]  Franco Fummi,et al.  Integrating RTL IPs into TLM Designs Through Automatic Transactor Generation , 2008, 2008 Design, Automation and Test in Europe.

[10]  Edward A. Lee,et al.  Taming heterogeneity - the Ptolemy approach , 2003, Proc. IEEE.

[11]  François Pêcheux,et al.  Holistic modeling of embedded systems with multi-discipline feedback: Application to a Precollision Mitigation Braking System , 2012, 2012 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[12]  Edward A. Lee Cyber Physical Systems: Design Challenges , 2008, 2008 11th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC).

[13]  A. Varga,et al.  THE OMNET++ DISCRETE EVENT SIMULATION SYSTEM , 2003 .